A multiobjective model for locating undesirable facilities
Annals of Operations Research - Special issue on locational decisions
A genetic algorithm for the generalised assignment problem
Computers and Operations Research
The Maximin-Maxisum Network Location Problem
Computational Optimization and Applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Discrete location problems with push-pull objectives
Discrete Applied Mathematics
Discrete facility location and routing of obnoxious activities
Discrete Applied Mathematics - International symposium on combinatorial optimisation
Multicriteria Optimization
Trade-offs Between Customer Service and Cost in Integrated Supply Chain Design
Manufacturing & Service Operations Management
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A bi-objective iterated local search heuristic with path-relinking for the p-median problem
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
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Colombian environmental authorities are exploring new alternatives for improving the disposal of hospital waste generated in the Department of Boyacá (Colombia). To design this hospital waste management network we propose a biobjective obnoxious facility location problem (BOOFLP) that deals with the existing tradeoff between a low-cost operating network and the negative effect on the population living near the waste management facilities. To solve the BOOFLP we propose a hybrid approach that combines a multiobjective evolutionary algorithm (NSGA II) with a mixed-integer program. The algorithms are compared against the Noninferior Set Estimation (NISE) method and tested on data from Boyacá's hospital waste management network and publicly available instances.